Automatically Detecting an Event and Determining Whether the Event Is a Particular Type of Event

1. A method, comprising: receiving, by a device and from one or more other devices, one or more images that depict one or more events occurring at a location; detecting, by the device, a first event of the one or more events depicted in the one or more images; processing, by the device, first data received from the one or more other devices; determining, by the device and based on processing the first data, whether one or more first terms in the first data match one or more second terms in metadata associated with the one or more images; determining, by the device and based on determining that the one or more first terms match the one or more second terms, a first score that indicates a likelihood that the first event is an anomalous event; processing, by the device, second data received from the one or more other devices, the second data being associated with a second event, and the second data comprising at least one of: data from a sensor, data from a wearable device, data from a mobile device, or data from a handheld device; determining, by the device and based on processing the second data, whether one or more third terms associated with the second event match one or more fourth terms associated with the first event; determining, by the device and based on determining that the one or more third terms match the one or more fourth terms, a second score that indicates a similarity between the first event and the second event; and performing, by the device, an action based on the first score and the second score.

2. The method of claim 1 , where the one or more images are from a digital video camera.

3. The method of claim 1 , where the first data comprises data from a historical server device.

4. The method of claim 1 , where the first data comprises data from an external server device.

5. The method of claim 1 , where the first data comprises data from a social media server device.

6. The method of claim 1 , where the second data comprises data from an external server device.

7. The method of claim 1 , where the second data comprises data from a social media server device.

8. The method of claim 1 , where performing the action comprises: transmitting a report to at least one of: the wearable device, the mobile device, or the handheld device.

9. A device, comprising: one or more processors to: receive an image from an image capture system, the image depicting an event; detect the event depicted in the image using an image processing technique; process first data received from one or more other devices, determine, based on processing the first data, whether one or more first terms in the first data match one or more second terms in metadata associated with the image; determine, based on determining that the one or more first terms match the one or more second terms, a score that indicates whether the event is an anomalous event; process second data received from the one or more other devices, the second data being associated with another event, and the second data comprising at least one of: data from a sensor, data from a wearable device, data from a mobile device, or data from a handheld device; determine, based on processing the second data, whether one or more third terms associated with the other event match one or more fourth terms associated with the event; determine, based on determining that the one or more third terms match the one or more fourth terms, a similarity between the event and another event using the second data; adjust the score based on determining the similarity between the event and the other event; and perform an action based on the score.

10. The device of claim 9 , where the one or more first terms include one or more terms that are included in data associated with a message.

11. The device of claim 9 , where the one or more processors, are to: process the first data using a sentiment analysis, the first data including data associated with a message or a social media post; identify a sentiment associated with the message or the social media post; and determine a result of the sentiment analysis based on identifying the sentiment; and where the one or more processors, when determining the score, are to: determine the score based on the result of the sentiment analysis.

12. The device of claim 9 , where the one or more processors, are to: structure the first data and the second data using a knowledge base; identify a quantity of nodes of the knowledge base associated with the first data and the second data; and determine whether the quantity of nodes satisfies a threshold; and where the one or more processors, when determining the similarity between the event and the other event, are to: determine the similarity between the event and the other event based on determining that the quantity of nodes satisfies the threshold.

13. The device of claim 9 , where the one or more processors, when performing the action, are to: transmit a message to a user device based on the score, the message including the first data.

14. A computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive, from one or more other devices, one or more images that depict one or more events occurring at a location; detect a first event of the one or more events depicted in the one or more images; process first data received from the one or more other devices; determine, based on processing the first data, whether one or more first terms in the first data match one or more second terms in metadata associated with the one or more images; determine, based on determining that the one or more first terms match the one or more second terms, a first score that indicates a likelihood that the first event is an anomalous event; process second data received from the one or more other devices, the second data being associated with a second event, and the second data comprising at least one of: data from a sensor, data from a wearable device, data from a mobile device, or data from a handheld device; determine, based on processing the second data, whether one or more third terms associated with the second event match one or more fourth terms associated with the first event; determine, based on determining that the one or more third terms match the one or more fourth terms, a second score that indicates a similarity between the first event and the second event; and perform an action based on the first score and the second score.

15. The computer-readable medium of claim 14 , where the one or more images are from a digital video camera.

16. The computer-readable medium of claim 14 , where the first data comprises data from a historical server device.

17. The computer-readable medium of claim 14 , where the first data comprises data from an external server device.

18. The computer-readable medium of claim 14 , where the first data comprises data from a social media server device.

19. The computer-readable medium of claim 14 , where the second data comprises data from an external server device.

20. The computer-readable medium of claim 14 , where the second data comprises data from a social media server device.